Various methods exist for viewing and manipulating data to create a three-dimensional image. As those skilled in the art will appreciate, such three-dimensional images provide a valuable tool to the medical professional in a manner which is non-invasive, and which is therefore considered to be of very low risk to the patient.
Tomographic imaging techniques for use in medical applications are well known. Examples of such techniques include magnetic resonance imaging (MRI), computer aided tomography (CAT), and positron emission tomography (PET). In each of these techniques, a multi-dimensional array of volume information or a plurality of cross-sectional, two-dimensional images, i.e., slices, of a body portion are generated and processed so as to provide a three-dimensional model of the imaged body portion.
Although such three-dimensional imaging techniques have proven extremely useful for their intended purposes, they still possess inherent deficiencies which detract from their overall effectiveness. Current methods attempt to project the generated three-dimensional image directly onto a screen and thus do not allow the end user to view the three-dimensional figure from arbitrary angles or manipulate the transparency of various objects to allow underlying objects to be easily viewed. In addition, current systems do not allow the end user to easily manipulate the images.
Another problem with current methods is that it is frequently difficult to interpret the viewed two-dimensional slices or images when the anatomical structures of interest are surrounded by and/or intermixed with various other anatomical structures. The undesirable presence of such superfluous imagery only complicates the image, making it much more difficult to view and interpret the desired imagery.
For example, viewing the delicate portions of the vascular system is typically difficult since veins, arteries, and capillaries are intermixed with surrounding tissue. This makes it very difficult to distinguish the desired portions of the vascular system from surrounding tissue. Often, only slight changes in the intensity of the image distinguish a desired anatomical structure from surrounding tissue.